A Novel Compressive Sensing Approach to Simultaneously Acquire Color and Near-infrared Images on a Single Sensor

Sensors of most digital cameras are made of silicon that is inherently sensitive to both the visible and near-infrared parts of the electromagnetic spectrum. In this paper, we address the problem of color and NIR joint acquisition. We propose a framework for the joint acquisition that uses only a single silicon sensor and a slightly modified version of the Bayer color-filter array that is already mounted in most color cameras. Implementing such a design for an RGB and NIR joint acquisition system requires minor changes to the hardware of commercial color cameras. One of the important differences between this design and the conventional color camera is the post-processing applied to the captured values to reconstruct full resolution images. By using a CFA similar to Bayer, the sensor records a mixture of NIR and one color channel in each pixel. In this case, separating NIR and color channels in different pixels is equivalent to solving an under-determined system of linear equations. To solve this problem, we propose a novel algorithm that uses the tools developed in the field of compressive sensing. Our method results in high-quality RGB and NIR images (the average PSNR of more than 30 dB for the reconstructed images) and shows a promising path towards RGB and NIR cameras.